Team: 11
School: Everest Academy
Area of Science: Data Visualization
Interim:
The purpose of this project is to dynamically visualize popular internet searches via Google Trends[1], by compiling them into a data visualization illustrated by the image results from those terms. By "dynamic," I am referring to the visualization updating in real-time as trending searches change.
I will be developing this in Python. Unfortunately, Google Trends does not offer an API for Python (or any other language), but General Mills has published an unofficial Python API[2]. Dynamically visualizing data is not a new idea[3], but doing so in a fully automated way remains an eternally underused and underrated angle.
I have researched into other trend platforms, but none have Google's market share dominance and so would provide limited insight into more frequently searched terms. I looked into a couple other library options, and found one obvious choice for Python for tapping into Google Trends. I am currently taking a crash course[4] on Python.
I expect to produce a demo showcasing the basic functionality (dynamic/real-time visualization of Google Trends data). The lack of official API support means that, for example, the prototype may not be scalable or distributable, as well as not having much/any additional functionality (such as that found in Polymath Technologies' Optima[5]) that would be useful for an end user such as hedge fund managers.
[1] https://trends.google.com/trends/trendingsearches/realtime?geo=US&category=all
[2] https://github.com/GeneralMills/pytrends
[3] https://informationisbeautiful.net/beautifulnews/
[4] https://www.youtube.com/watch?v=sxTmJE4k0ho
[5] https://www.finextra.com/pressarticle/35609/polymath-unveils-real-time-visualisation-tool-for-hedge-funds
Team Members: Emily Edington
Mentor: Creighton Edington
Team Members:
Sponsoring Teacher: Creighton Edington